6.867 Machine Learning (Fall 2003)

This introductory course on machine learning will give an overview
of many concepts, techniques, and algorithms in machine learning,
beginning with topics such as linear regression and ending up with
more recent topics such as boosting, support vector machines, hidden
Markov models, and Bayesian networks. The course will give the student
the basic ideas and intuition behind modern machine learning methods
as well as a bit more formal understanding of how, why, and when they
work. The underlying theme in the course is statistical inference as
it provides the foundation for most of the methods covered.